高频部分液体通气对吸入性损伤犬呼吸功的影响

目的　观察高频喷射通气结合小剂量氟碳 (3ml/kg)液体通气对吸入性损伤犬呼吸的功影响。方法　将 16条犬经蒸气吸入造成吸入性损伤模型 ,并随机分为两组 ,即对照组和治疗组。两组动物致伤后均行高频喷射通气 ,但治疗组动物同时经气管导管将氟碳液体 (3ml/kg)缓慢注入肺内 ,在 90min内测机械通气功 (WOBvent)。结果　治疗组在给予小剂量氟碳后的WOBvent与致伤后比较差异无显著意义 (P >0 0 5 ) ,对照组治疗后的WOBvent与致伤后比较差异亦无显著意义 (P >0 0 5 ) ,治疗组与对照组各时间点的WOBvent比较差异均无显著意义 (P >0 0 5 )。结论　高频喷射通气合并小剂量氟碳 (3ml/kg)部分液体通气并不增加动物的呼吸功。     

主动按压减压结合高频通气对心肺复苏犬的循环效应影响

目的　比较标准心肺复苏、主动按压减压心肺复苏、主动按压减压结合高频通气心肺复苏三种复苏法对心肺复苏循环效应影响 ;评价主动按压减压结合高频通气用于心肺复苏的可行性。方法　将9条犬经电击致颤制成心搏骤停模型 ,每只犬先后实施三种复苏法 ,①标准心肺复苏 ;②主动按压减压心肺复苏 ;③主动按压减压结合高频通气心肺复苏 ,实验顺序由随机法确定 ,每种复苏方法进行 5min ,待循环动力学稳定后记录收缩压、舒张压、心输出量。结果　收缩压、舒张压、心输出量均为主动按压减压结合高频通气模式大于主动按压减压心肺复苏模式 (P <0 0 1) ;主动按压减压心肺复苏模式大于标准心肺复苏模式 (P <0 0 1)。标准心肺复苏模式和主动按压减压心肺复苏模式胸外按压停顿期血压降至零 ,而主动按压减压结合高频通气心肺复苏模式血压持续稳定。结论　主动按压减压心肺复苏优于标准心肺复苏模式。主动按压减压结合高频通气心肺复苏模式既可产生较高的动脉血压、心输出量 ,又可提供充分的气体交换 ,值得进一步研究和推广应用     

The multiscale character of evoked cortical activity

Both the architecture and the dynamics of the brain have characteristic features at different spatial scales. However, the existence, nature and function of dynamical interdependencies between such scales have not been investigated. We studied the multiscale properties of functional magnetic resonance imaging (fMRI) data acquired while human subjects viewed a visual image. Traditional "region of interest" analysis of this data set revealed evoked activity in primary and extrastriate visual cortex. Wavelet transform in the spatial domain provides a multiscale representation of this evoked brain activity. Studying the correlation structure of this representation revealed strong and novel interdependencies in these data within and between different spatial scales. We found that such correlations are stronger than those evident in the original data and comparable in magnitude to those obtained after Gaussian smoothing. However, analysis of the data in the wavelet domain revealed additional structure such as positive correlations, strong anti-correlations and phase-lagged interdependencies. Statistical significance of these effects was inferred through nonparametric bootstrap techniques. We conclude that the spatial analysis of functional neuroimaging data in the wavelet domain provides novel information which may reflect complex spatiotemporal neuronal activity and information encoding. It also affords a quantitative means of testing hierarchical and multiscale models of cortical activity.     

一种高灵敏喷射式Ru(bpy)32+电化学发光流动体系的构建

目的:在改进的喷射式电化学发光流动注射系统的基础上,构建了一种高灵敏的Ru(bpy)32+电化学发光体系.方法:考察非离子表面活性剂Triton X-100、Tween-20以及共反应物TPA、DBAE对Ru(bpy)32+电化学发光体系的影响.结果:建立了含有0.05％ Triton X-100或0.1％ Tween-20添加剂的Ru(bpy)32+-DBAE喷射式电化学发光体系,该体系检测范围宽、检测灵敏度高达5×10-15 mol/L.结论:该体系比常规Ru(bpy)32+-TPA体系具有更高的稳定性和环境友好性,有望用于后续临床免疫、基因电化学发光检测系统的建立.     

轴节类器械不同清洗方法的效果观察

目的探讨轴节类医疗器械的有效清洗方法,保证再生器械灭菌质量。方法将回收的450件轴节类器械随机分为A、B、C三组各150件,每组组织剪、止血钳、持针器各50件。器械在流动水下充分冲洗后,A组用全自动清洗消毒机清洗;B组浸泡于多酶清洗剂10min,人工刷洗后再用全自动清洗消毒机清洗;C组用超声机加酶清洗后人工刷洗,进而手工漂洗再高温煮沸。结果三组清洗后目测合格率及潜血试验阳性率比较,差异有统计学意义(均P<0.01),其中C组潜血试验阳性率显著低于A、B组(均P<0.0125)。三组清洗后器械咬合面、关节处潜血试验阳性率比较,差异有统计学意义(均P<0.01),C组上述部位潜血试验阳性率显著低于A、B组(均P<0.0125)。结论超声清洗机加酶清洗后进行手工刷洗,可有效去除残留物,是轴节类器械较理想的清洗方法。     

两种血培养瓶在昆明市某医院近5年艾滋病患者血流感染病原分析中的应用

目的了解昆明某医院近5年住院艾滋病患者血流感染病原分布。对比两种血培养瓶对不同病原菌的检出情况。 方法对2013-2017年住院艾滋病患者使用两种血培养瓶(普通血培养和分枝杆菌/真菌血培养)的培养结果进行回顾分析。 结果普通血培养阳性率5.8%,病原菌前5位为马尔尼菲篮状菌、新生隐球菌、凝固酶阴性葡萄球菌、金黄色葡萄球菌、大肠埃希菌。分枝杆菌/真菌血培养阳性率12.8%,病原菌前5位为分枝杆菌、马尔尼菲篮状菌、新生隐球菌、大肠埃希菌、凝固酶阴性葡萄球菌。 结论2013-2017年艾滋病患者血流感染病原菌以真菌为主,马尔尼菲篮状菌和新生隐球菌为真菌感染的主要菌种;应用分枝杆菌/真菌血培养瓶,分枝杆菌检出率4.8%,分枝杆菌是引起艾滋病患者血流感染仅次于真菌的病原菌,分枝杆菌引起的血流感染不容忽视;普通血培养瓶配合分枝杆菌/真菌血培养瓶的使用可以增加艾滋病患者血流感染病原菌检出机会。     

From the Cover: Synchronization in human musical rhythms and mutually interacting complex systems

Though the music produced by an ensemble is influenced by multiple factors, including musical genre, musician skill, and individual interpretation, rhythmic synchronization is at the foundation of musical interaction. Here, we study the statistical nature of the mutual interaction between two humans synchronizing rhythms. We find that the interbeat intervals of both laypeople and professional musicians exhibit scale-free (power law) cross-correlations. Surprisingly, the next beat to be played by one person is dependent on the entire history of the other person’s interbeat intervals on timescales up to several minutes. To understand this finding, we propose a general stochastic model for mutually interacting complex systems, which suggests a physiologically motivated explanation for the occurrence of scale-free cross-correlations. We show that the observed long-term memory phenomenon in rhythmic synchronization can be imitated by fractal coupling of separately recorded or synthesized audio tracks and thus applied in electronic music. Though this study provides an understanding of fundamental characteristics of timing and synchronization at the interbrain level, the mutually interacting complex systems model may also be applied to study the dynamics of other complex systems where scale-free cross-correlations have been observed, including econophysics, physiological time series, and collective behavior of animal flocks.In his book Musicophilia, neurologist Oliver Sacks writes: “In all societies, a primary function of music is collective and communal, to bring and bind people together. People sing together and dance together in every culture, and one can imagine them having done so around the first fires, a hundred thousand years ago” (1). Sacks adds, “In such a situation, there seems to be an actual binding of nervous systems accomplished by rhythm” (2). These thoughts lead to the question: Is there any underlying and quantifiable structure to the subjective experience of “musical binding”? Here, we examine the statistical nature of musical binding (also referred to as musical coupling) when two humans play rhythms in synchrony.Every beat a single (noninteracting) layperson or musician plays is accompanied by small temporal deviations from the exact beat pattern, i.e., even a trained musician will hit a drum beat slightly ahead or behind the metronome (with a SD of typically 5–15 ms). Interestingly, these deviations are statistically dependent and exhibit long-range correlations (LRC) (3, 4). Listeners significantly prefer music mirroring long-range correlated temporal deviations over uncorrelated (white noise) fluctuations (5, 6). LRC are also inherent in the reproduction of both spatial and temporal intervals of single subjects (4, 7–9) and in musical compositions, such as pitch fluctuations (a simple example of pitch fluctuations is a melody) (10, 11) and note lengths (12). The observation of power law correlations in fluctuations of pitch and note length in compositions reflects a hierarchical, self-similar structure in these compositions.In this article, we examine rhythmic synchronization, which is at the foundation of musical interaction, from orchestral play to audience hand-clapping (13). More specifically, we show that the interbeat intervals (IBIs) of two subjects synchronizing musical rhythms exhibit long-range cross-correlations (LRCCs), which appears to be a general phenomenon given that these LRCC were found both in professional musicians and in laypeople.The observation of LRCCs may point to characteristics of criticality in the dynamics of the considered complex system. LRCCs are characterized by a power law decay of the cross-correlation function and indicate that the two time series of IBIs form a self-similar (fractal) structure. Here, self-similarity implies that trends in the IBIs are likely to repeat on different timescales, i.e., patterns of IBI fluctuations of one musician tend to reproduce in a statistically similar way at a later time—even in the other musician’s play. A variety of complex systems exhibit LRCCs; examples include price fluctuations of the New York Stock Exchange (where the LRCCs become more pronounced during economic crises) (14–16), heartbeat and EEG fluctuations (15, 17), particles in a Lorentz channel (18), the binding affinity of proteins to DNA (15), schools of fish (19), and the collective response of starling flocks (20, 21). The origin of collective dynamics and LRCCs based on local interactions often appears elusive (20), and is the focus of current research (19, 21). Of particular interest are the rules of interactions of the individuals in a crowd (22, 23) and transitions to synchronized behavior (16, 24). We introduce a stochastic model for mutually interacting complex systems (MICS) that generates LRCCs and provides a physiologically motivated explanation for the surprising presence of long-term memory in the cross-correlations of musical performances.Interbrain synchronization has received growing attention recently, including studies of interpersonal synchronization (see ref. 4 for an overview), coordination of speech rhythm (25), social interactions (26), cortical phase synchronization while playing guitar in duets (27, 28), and improvisation in classical music performances (29).Notably, the differences between the beats of two musicians are on the order of only a few milliseconds, not much larger than the typical duration of a single action potential (∼1 ms). The neurophysical mechanisms of timing in the millisecond range are still widely open (30, 31). EEG oscillatory patterns are associated with error prediction during music performance (32). Fine motor skills, such as finger-tapping rhythm and rate, are used to establish an early diagnosis of Huntington disease (33). The neurological capacity to synchronize with a beat may offer therapeutic applications for Parkinson disease, but the mechanisms are unknown to date (34). This study offers a statistical framework that may help to understand these mechanisms.     

Risk factors and microbial profile of central venous catheter related blood stream infection in medical cardiac care units,National Heart Institute,Egypt

Introduction

Catheter related blood stream infection (CRBSI) is the main complication of central venous catheter (CVC) use. The aim of the study is to improve the safety of patients with central venous catheter in National Heart Institute (NHI) medical cardiac care units.